Predicting responses of resources to demand response signals and having comfortable demand responses

ABSTRACT

An approach where a utility/ISO may dispatch demand response (DR) resources in real time without notification of a DR event. DR dispatches may involve sending specific load level commands to power generators that can respond to such commands in a predictable fashion. DR resources do not necessarily have the same level of control or predictability in their load responses. Accuracy of predicting a DR resource&#39;s response to a DR signal may be improved by restricting the DR signal to predefined finite values and, for each predefined finite value, have the DR resource continuously report back what its load response will be if one of those signal values is sent as a DR signal. A DR performed against a home may result in discomfort. But there may be a sufficient recovery rate for regaining the setpoint of a thermostat to attain comfort of the home within a reasonable period of time.

BACKGROUND

The present disclosure pertains to utility resources and particularly toassessment and distribution of the resources. More particularly, thedisclosure pertains to beneficial management of resources and theirloads.

SUMMARY

The disclosure reveals an approach where a utility/ISO may dispatchdemand response (DR) resources in real time without prior notificationof a DR event. Fast DR dispatches may involve sending specific loadlevel commands to power generators that have little problem respondingto such commands in a fairly predictable fashion. DR resources do notnecessarily have the same level of control or predictability in theirload responses. Accuracy of predicting a DR resource's response to a DRsignal may be improved by restricting the DR signal to predefined finitevalues and, for each predefined finite value, have the DR resourcecontinuously report back what its load response will be if one of thosesignal values were to be sent as a DR signal. A DR performed against ahome may result in discomfort. But there may be a sufficient recoveryrate to regain a setpoint of a home thermostat so as to attain comfortof the home within a reasonable period of time.

BRIEF DESCRIPTION OF THE DRAWING

FIG. 1 is a diagram of a layout having a utility/independent systemoperator (ISO) and demand response resources;

FIG. 2 is a diagram of a table showing a basis of the scoring functionfor selecting demand response resources;

FIG. 3 is a diagram of a graph indicating activity of an operatorinterface showing a current state of resources and a set of options forvarious levels for dispatches;

FIG. 4 is a diagram of an implementation of demand response and resourcesignals in a demand response arrangement of a utility/ISO and aresource;

FIG. 5 is a diagram of a demand response arrangement having remotecontrol relative to a utility and a resource incorporating incentivesfor a resource to not opt out or to opt in a demand response program;

FIG. 6 is a diagram of a utility/ISO that may utilize a demand responsemanagement system for providing utility defined signals to a demandresponse resource;

FIG. 7 is a diagram of a utility/ISO that may utilize a demand responsemanagement system for providing customer defined signals to a demandresponse resource; and

FIG. 8 is a diagram of a utility/ISO that may utilize the demandresponse management system for translating utility defined signals tocustomer defined signals for the demand response resource.

DESCRIPTION

The present system and approach may incorporate one or more processors,computers, controllers, user interfaces, wireless and/or wireconnections, and/or the like, in an implementation described and/orshown herein.

This description may provide one or more illustrative and specificexamples or ways of implementing the present system and approach. Theremay be numerous other examples or ways of implementing the system andapproach.

Automated demand response (ADR) programs may be used in a number ofdifferent customer market segments ranging from large commercial andindustrial to small commercial and residential. A diagram of FIG. 1shows a layout 10 of a utility/ISO 11 and DR resources 12. Utility/ISO11 may enroll customers into demand response (DR) programs and modelthem as so called DR resources 12 that they can call upon when it isnecessary for utility 11 to initiate a DR event 13. Calling upon a DRresource 12 typically means that the utility/ISO 11 “dispatches” the DRresources by sending them DR signals 14 which affect their loadconsumption in some predictable fashion. A pre-cursor to initiating a DRevent 14 is the establishment of a set of objectives that need to beaccomplished during the DR event. Such objectives may include thefollowing items: 1) A specific amount of load response over some periodof time (load responses may entail both reduced and increased levels ofconsumption); 2) Loads associated with a specific grid and/or geographiclocations; 3) A specific type of loads; and 4) Loads with minimumresponse times and latencies.

When a utility 11 initiates a DR event 13, the utility may typicallyselect some subset of the available DR resources 12 from the collectionof all possible DR resources that meets the objectives as outlinedabove. Each DR resource 12 may have both capabilities and associatedcosts with using that resource during an event so the problem to besolved is how best to minimize the overall cost of a collection of DRresources while still using their capabilities to satisfy the overallobjectives of the DR event 13. Furthermore, in the case of so called“Fast DR”, which may require dispatches to happen in real time, it maybe necessary that the DR resource 12 selection process be automated andnot require human operator involvement.

The present system may solve the requirement for optimizing andautomating the process of DR resource 12 selection for DR events 13 byutilizing a scoring function that can be easily applied against eachindividual resource to create a ranking of each resource. The scoringfunction may take into account both the capabilities and the costsassociated with using the resource. In other words, the DR resource mayhave a set of attributes that are used as factors in the scoringfunction. In some cases, the DR resource attributes may be invariant tospecific DR events (e.g., geographic location), but in other cases theattribute may have different relevance or values depending upon thespecific DR event. For example, if it is a requirement that the DR eventhappens between 2 pm and 4 pm, but a specific DR resource is notavailable during those hours, then it should receive a score that ranksit in such a manner that it is not chosen.

Furthermore, the scoring function may have a form that supportsoperations by the utility operator. Such operations may incorporate: 1)An ability to select which resource attributes may be relevant in theselection process; 2) An ability to select how the resource attributesmay be applied in the scoring function; and 3) An ability to increase ordecrease the relevance of a resource attribute in the overall score of aDR resource.

The form of the scoring function described below may support virtuallyall these features. FIG. 2 is a diagram of a table 16 showing a basis ofthe scoring function.

The selection process may then be easily automated by simply selectingenough of the highest ranked resources that satisfy the load objectivesof the DR events 13.

One step may be to model the DR resources 12 by characterizing them witha set of attributes that specify their load consumption capabilities andtheir costs. A DR resource's capabilities may be characterized with thefollowing attributes (among others).

1) Forecasted load profiles under normal conditions. These may be thepredicted levels of load consumption under normal conditions (i.e., notduring DR events) as a function of time. Such forecasts may sometimes bereferred to as baselines. It may also be dependent upon not only timebut may incorporate other factors such as weather or buildingoperational state in view of occupancy.

2) Forecasted load profile capabilities during DR events 13. The profilecapabilities may be the predicted levels of load consumption during DRevents as a function of time. It could be as simple as a single value oras complex as a multi-dimensional load profile. A load profile'sdimensions might include things such as time and dispatch levels.

3) Real time load profiles. The load profiles may be determined in realtime based upon real-time feedback from a resource. The profiles mayinclude such things at the current load consumption (i.e., metering) andthe current state of the load controller.

The current state of the load controller may provide additional insightsinto what may be possible if a DR signal 14 is sent to resource 12. Forexample, if resource 12 is a light and the light is already off then theutility will not be able to get that resource to reduce its consumptionby sending it a signal 14.

4) Availability schedules may give the dates and times that theresources are available. A DR resource 12 may also have a costassociated with using that resource. Within the context of thisapproach, the term cost may be used in a general sense and representmany different dimensions including the following items (among others).

5) Utility fixed financial cost associated with using the resource maybe the amount of fixed money that must be spent by the utility 11 for aresource 12 to participate in an event 13.

6) Utility performance based financial costs may be the costs associatedwith how much money utility 11 must spend to use resource 12 based uponits performance during an event 13. The costs may be based upon suchfactors as time of day and amount of load response with respect to somebaseline. The costs may also be based upon some bid that was submittedby the resource owner.

7) Resource owner financial cost may be another item.

8) Resource owner inconvenience cost may be a qualitative cost thatreflects the impact on the resource owner during event 13. The cost mayreflect things such as discomfort or necessary changes in the resourcesowner's operations.

9) Mileage left on resource 12. Often the amount of time or frequencythat a resource can be called upon may be constrained either by the useror by the utility program. For example, a resource may be limited totwelve DR events 13 in the course of a year. Thus, a resource that hasbeen called for eight events may have less remaining mileage than onethat has only been called for four events.

Other attributes may be used in addition to or in lieu of the one ormore above-noted ones. Each of the above attributes may be used as afactor having a value in a scoring function to determine an overallscore of a resource within a context of specific DR events and theirobjectives.

The scoring function may take the following form as at least partiallyillustrated in table 16. F1, F2, . . . , Fn may be represent the scoringfactors. Each Fn, i.e., scoring factor, may correspond to a differentattribute of the DR resource and have a value from zero (0) to one (1)that represents how well that a selected individual attribute satisfiesthe overall objectives of a DR event 13. In general, a value of “one”means that a resource 12 has the highest possible relevance or valuewith respect to an attribute, and likewise a value of zero means that aresource 12 has the lowest possible value or relevance with respect tothe attribute. For example, if F1 represents financial cost then a valueof zero would mean that DR resource 12 may have the highest possiblefinancial cost (e.g., the most expensive of all resources) and a valueof one would mean that it is the cheapest of all resources.

Table 16 of FIG. 3 shows factors, values and attributes for determininga score for a DR resource. The attributes may be selected from the ninelisted above. Factors F1 through F9 may be associated with attributes,respectively. Values, which range from 0 to 1, may be represented by theletters A, B, C, D, E, F, G, H and I, respectively. A score for the DRresource 12 may be determining by adding up the values for each of thelisted attributes. Other attributes may be added. Some attributes may bedeleted. The scoring function may be customized with respect to needs ofthe demand response situation at hand. The score may be normalized forcomparison with the individual values of the attributes.

The different factors can be applied in the sco (standard choice offeror stranded cost obligation) approach.

In the case of a so-called “Fast DR”, the utility may dispatch the DRresources 12 in real time without any prior notification of a DR event13. Fast DR dispatches may involve sending specific load level commands(e.g., 15 MW) to generators that have no problem responding to suchcommands in a fairly predictable fashion. Demand response resources 12unfortunately do not necessarily have the same level of control orpredictability in their load responses. It can be difficult to knowprecisely what a load response from the DR resource will be at anyinstance because the load response may be dependent upon the followingitems: 1) The DR signal 14 that is being sent; 2) The current state ofthe loads being controlled by the DR resource 12; 3) The DR strategiesbeing implemented by the DR resource 12; and 4) Extraneous factors suchas weather.

The utility/ISO 11 may perform some sort of regression analysis on pastperformance of the DR resource 12 to predict what may happen in thefuture (e.g., baselines). This approach may have major flaws in thatthere is often a lack of history to properly predict what the behaviorwill be and the predictions furthermore do not take into considerationthe current state of the DR resource 12. In short, the predictions arenot necessarily very accurate.

The present approach may improve the accuracy of predicting a DRresource's response to a DR signal 14 by applying the followingprinciples: 1) Restrict the DR signal 14 to a set of predefined finitevalues (e.g., NORMAL, MODERATE, HIGH, and so forth); and 2) For each ofthe predefined finite values, have the DR resource 12 continuouslyreport back what its load response will be if one of those signal valueswere to be sent as a DR signal.

The present approach may have the following benefits. 1) Since the DRsignal 14 can be of a set of finite values, the DR resource 12 does notnecessarily have to support a continuum of values and may more closelymatch the way in which DR strategies are typically developed. 2) The setof finite values may make it easier for the DR resource 12 to determinewhat its DR response will be at any given time. 3) Since the DR resource12 is reporting its response in the same terms as the signal itself,there is no need for the utility/ISO 11 to model the resources' DRstrategies or loads.

The utility/ISO may use a demand response management system (DRMS) formanaging its DR programs. The DRMS may be responsible for presenting theutility/ISO 11 operator with a user interface to manage the DR programand for interacting with the DR resource automation systems to both sendDR signals 14 to and receive feedback from DR resource 12. In the caseof a fast DR, the operator may have an interface as shown in FIG. 3 thatmay show the current state of the resources and present the operatorwith a set of options for what levels they may dispatch the resourcesto. In the case of FIG. 3, there is only a single DR resource 12 beingshown that may respond to DR signals 14 and the finite signal levels arelow, moderate, and high.

DR resource 12 may be in constant communications with the DRMS andcontinuously report what its load response in MW will be if it were toreceive any of the predefined signals. On the graph of the operatorinterface may be depicted the actual load response 26 versus time for DRresource 12 both past and potentially in the future. For times in thefuture, the different potential load responses may be shown as flatlines 21, 22, 23, 24 and 25 that are based upon feedback received fromDR resource 12. In this way, the operator may know precisely what the DRresource's potential load response will be in real time based upon themost accurate source of information, which may be DR resource 12 itself.

Although FIG. 3 only shows a single DR resource, the concept may beextensible to an aggregation of multiple resources. The potential DRresource responses may be aggregated together in the following ways. 1)The response values for each of the signal types may simply be addedtogether and the operator still may have only a small finite number ofpossible dispatch levels. 2) The various response levels or values maybe combined together in such a way that the operator has in essence amore refined number of levels that can be dispatched. With way 1, thenumber of levels that the operator can use may correspond directly to anumber of levels supported by the resources. For example, if all of theresource support was just a MEDIUM or HIGH level, then the operator mayonly have available to her/him a setting of MEDIUM or HIGH. If theoperator chooses MEDIUM, then the same medium signal may be sent to allof the resources and the expected response can be as simple as theMEDIUM level of each resource added together. In way 2, the operator canset the desired amount of shed to send and each resource may be sent adifferent signal to achieve that level. Resource 1 might get a MEDIUMsignal and resource 2 might get a HIGH signal. The point of way 2 isthat the combinatorics of all different levels of all the differentresources may lend to a much larger number and more refined number ofsettings that the operator can specify.

When using way 2), with enough DR resources in the aggregate group, theoperator may have what would appear to be a continuous number ofdifferent dispatch levels that could be chosen including from those thatwould only dispatch some subset of the available resources. Thesecombinations of resources may be selected in some automated fashion sothat the operator would only need to select the level that is desiredfor dispatch and that the DRMS may select the optimum subset of DRresources 12 to fulfill that objective.

The approach for the DRMS to send DR signals and receive feedback fromthe resources may use established specifications such as an open ADR.

A comfortable demand response may be noted. DR performed against a homemay result in discomfort for a homeowner. Part of a goal may be arecovery rate sufficient to regain a setpoint of a thermostat in thehome so as to attain comfort of the home within a reasonable period oftime.

Each home may recover to the setpoint differently because of its size,tightness of the construction, size of HVAC equipment, and much more.

A ramp rate score for a home or business may be created. This score maybe used to determine the level of demand response that can be performed.For instance, a house #1 may be old and leaky. When a DR event isperformed, the temperature of this house may change+5 degrees during theDR event. After the event, the time to reach setpoint may be 2 hours.

In another instance, a house #2 may be a new home and built tightly.When a DR is performed, the temperature of this house may change by +5degrees during the DR event. After the event, the time to reach setpointmay be 1 hour.

DR events may be set as being customized for the home by understandingthe setpoint recovery rate. By performing a test DR event and measuringthe recovery to a setpoint, an algorithm may be created and a rating canbe placed on a home. The rating may be used to apply a new methodologyof DR by the utility. A utility operator may determine that there needsto be a certain amount, e.g., 1 KW, of shed. The operator may select atemperature for an off-set; however, the operator may also set therecovery time for the home.

A utility operator may select plus five (+5) degrees and a recovery tosetpoint of one hour (knowing that the homeowners will want a normalplanned temperature when they return home). When applying the DR event,homes may be grouped by both temperature and recovery rate.

Home 1 may only have a setback of 2.5 degrees because the recovery takeslonger in this home. Home 2 may actually have a setback of 6 degreesbecause the recovery takes a shorter time in this home.

The homeowners in both instances may be sent a message via text, emailor phone or phone app. The message may state the time of the DR event,temperature off-set, and temperature anticipated recovery time.

Utilities may interact with their customers during DR events and sendthem information (DR signals) during a DR event. A particular type ofmessage may be sent to a customer in a DR event that may incentivizethem to participate in a DR event.

An effective resource is especially critical when communities areconfronted with a scarcity of a resource in question. It may be notedthat “resource” is a term which may have several senses or meanings.“Resource” may refer to energy, commodity, product, load, and so on. Inanother sense or meaning, “resource” such as a demand response (DR)resource may refer to a customer, user, participant, facility, and soon. In the first mentioned sense, it may refer to electricity, water,gas and natural resources such as oil. A definition of “resource” may beextended to include such things such as water quality and air quality.In this regard, adequate water quality and air quality appear necessaryto support a self-sustaining environment.

Resource management, in several senses, may be necessary so that systemscan optimize the use of a limited resource. Currently, there are varioussystems for managing resources in various environments such asbuildings, apartments, industrial facilities, and computing systems.

One mechanism that might be used to encourage customers to reduce demandand thereby reduce the peak demand for electricity may be referred to asdemand response (DR). Demand response may refer to management of thedemand by customers in response to supply conditions. For example,electricity customers may reduce their consumption at critical timesand/or costs in response to market prices. These customers may beregarded as DR resources.

DR programs may require that a utility and/or independent systemoperator (ISO) deliver DR signals to customers or participants via acommunications channel. The programs may relate to a distribution ofresources such as, but not limited to, electricity, water and naturalgas.

DR signals may incorporate business level information, such as prices,reliability and shed levels. At some point, from the utility/ISO toloads in a facility, the business level information sent by theutility/ISO should be processed and used to execute a DR strategy andprogram for the facility.

DR programs may take many forms. They may differ from normal rates andtariffs in that the DR programs are designed to allow the utility/ISOtake specific actions to influence the load profiles of facilities thatparticipate in the DR programs at peak consumption times or periods on agrid. The peak consumption periods may cause critical grid reliabilityissues which should be addressed, but they may also trigger economicfactors where the price of electricity or other power commodity reachesa critical level which may be ameliorated by reducing the overallconsumption on the grid during those periods. The critical periods, inwhich the utility/ISO needs to influence a load profile of a facility,may be referred to as DR events.

A manner in which a utility/ISO may influence a load profile of afacility is to send out a DR signal which is specific to the DR event.DR signals may contain information related to businesses, controllingloads, pricing, and so on. There may be an automated DR where the DRsignals that are sent out by the utility/ISO are responded to in anautomated fashion. Loads within a facility may ultimately be affected byDR events via DR signals to which the facility acts upon or responds.The term “facility” may refer to virtually any location in which thereare loads influenced by DR events. A place where there are such loadsmay be regarded as a “DR resource”. The term “utility” may be used in ageneral sense to refer to a utility, independent system operator,service provider, and the like.

To provide a context for a mobile communication approach, the presentdisclosure reveals an implementation of DR signals which may be noted ina demand response arrangement 20 on a diagram of FIG. 4. System 20 andassociated software may be obtained and operated with one or morecomputers/controllers (controllers) 11, 12 and respective connections.The arrangement may be a system that is used by utilities/ISO's tomanage the operation of DR programs. A focus of the arrangement may beon the operational aspects of managing the selection, signaling andmonitoring of the DR resources that are participating in DR programs.The arrangement may be specifically designed to manage operations ofautomated DR programs.

There may be various types of interactions that might occur between theutility/ISO and a DR resource as part of a DR program. FIG. 4 is adiagram of an example interaction between a utility/ISO 11 and a DRresource (customer) 12. There may be DR signals 14 going fromutility/ISO 11 to DR resource 43. There may be DR resource signals 30incorporating information, such as load measurements, going from DRresource 12 to utility/ISO 11.

Terms such as customer, client, user, participant, DR resource, and liketerms, may be used, interchangeably or distinct from one another,depending on a context of a pertinent portion of a description or aclaim.

A description of DR signals 14 may be noted. At a high level, there mayoften be some sort of grid condition, be it economic or grid reliabilityin nature, which triggers a so-called DR event that requires some sortof interaction between the utility/ISO 11 and its customer 12. Thisinteraction may eventually trigger some sort of load control takingplace at a customer's facility. The interaction between the utility/ISO11 and the customer 12 may be mediated by DR signals 14 and DR resourcesignals 30, i.e., information such as measurements. Signals 14 and 30may represent communications between utility/ISO 11, and the DR resourceor customer 12. Information contained within DR signals 14 may dictatewhere much of the decision-making takes place relative to, for example,in how the initial grid condition, which triggered the DR event, resultsin the eventual load control.

A computer or controller may incorporate one or more inputs, aprocessor, a user interface incorporating a keyboard, a display and atouch screen, a memory, external connections such as an internet, one ormore outputs, and so forth. The computer or controller may be utilizedwith virtually all items in and pertinent to FIGS. 1-8.

Automated demand response (ADR) programs may be used in a number ofdifferent customer market segments ranging from large commercial andindustrial to small commercial and residential areas. The number ofsmall commercial facilities may typically outnumber the largercommercial and industrial facilities by an order of magnitude. Inaddition, the large commercial and industrial facilities may typicallyhave a dedicated staff and a larger budget for installing the equipmentnecessary to participate in ADR programs.

There may be a use of mobile devices to receive notifications and manageenergy based upon location. Utilities may increasingly communicate withtheir customers to enable them to better manage their energy usage.Communications of these utilities may range from sending their customersenergy prices to notifying them of upcoming DR events. In addition tosending their customers information, the utilities may also allow theircustomers to communicate with them to perform such functions as optingout of DR events or submitting bids as part of a DR program. Theincreased communications with utilities may create new opportunities forcustomers to save money by more actively controlling their energyconsumption. The approach by which a customer controls its energyconsumption may increasingly be done by some sort of automation in theform of a so-called energy management system (EMS). Any system that iscapable of controlling customer loads which consume energy may beconsidered as an EMS. An EMS may be as sophisticated as an industrialcontrol system or as simple as a thermostat. An EMS may be at a facilityof a customer.

One approach by which customers and utilities currently communicate maybe via the internet and some sort of computer system which requires thecustomer to be at some fixed location. Here, interactions may be viaemail or perhaps via some web-based application. Likewise, the way thatthe customer typically interacts with its EMS may be either directly atthe facility with the EMS, or via some computer-based terminal or userinterface. None of these interactions may be possible if the user is notat a location that will support the respective interaction.

What is needed is an approach for the customer to interact with theutility or an EMS at a facility in a more convenient fashion that isflexible and can go anywhere that the customer goes. In addition, sincethe customer is mobile, what is needed may be a way for the customer toreceive communications from the utility and to interact with a facilityEMS in a fashion that is relevant to its location. A location of themobile device may affect scenarios or a relevance of knowing somethingfrom an item at another location. Examples of where a customer'slocation is via the mobile device may be relevant in various scenariosrelating to utilities and facilities.

A customer with a mobile device may be moving between differentfacilities in which each facility has its own energy tariff or agreementwith potentially different utilities. Examples may include differentrates for different regions. A utility may decide to include differentfacilities in a DR event. A utility may have different agreements,obligations or options with two or more facilities resulting in messagesand data from the utility information system being different for variousenergy management systems of the two or more facilities, respectively.The differences of these items may be noticed by the customer atdifferent locations of the mobile device.

It may be noted that, relative to a facility, sub-systems that thecustomer may need to interact with may depend upon where the sub-systemsare located.

Certain devices, such as cell phones which are becoming more powerful,may become an effective approach for two-way communications and be aprime candidate to allow mobile customers to both communicate withutilities and to interact with their EMS's at various locations.

Mobile devices, such as smart phones, do not necessarily just send andreceive messages, but they may provide a way to run fairly sophisticatedapplications that can be used for remote monitoring and control ofenergy.

The present approach may use a location of a device as an element to putthe communications with the utility and the interactions with acustomer's EMS into a context that is most relevant to where thecustomer is currently located.

FIG. 5 is a diagram of a use case. The diagram may pertain to energyrelated interactions. The diagram shows a facility manager (FM) 31 thatmay be responsible for managing the operations of a facility 12 as itrelates to energy consumption. The facility manager 31 may be a personresponsible for spending virtually all of his or her time managing alarge facility operation, or manager 31 could simply be a small businessowner that does nothing more than adjusts its thermostat and lights. FM31 may be at various locations during the course of the day either on oroff site of a facility. FM 31 may carry a mobile device (MD) 33. MD 33may have the following characteristics. It may be a computing devicethat is easy to transport around, such as a cell phone, pad, smartphone, tablet or laptop. MD 33 may have a way to communicate wirelesslyusing technologies such as cellular media or WiFi.

MD 33 may have some sort of user interface that can display data ormessages communicated via the wireless communications and receive inputsfrom the FM 31 that can be transmitted on a wireless communicationschannel.

MD 33 may have a way to run applications to support the user interfaceeither natively or using some sort of web-based browser technology. MD33 may have a way to determine the location of the device, either by thedevice itself or by the system with which the device is communicating.

Facility manager 31 may have a mobile device 33 for communication withan energy management system or sub-system (EMS) 34 of a facility 12 andwith a utility information system or sub-system (UIS) 36 of utility 11.Mobile device 33 may be used by facility manager 31 to send commands anddata 44 to energy management system 34 and to receive messages and data45 from energy management system 34. Also, mobile device 33 may be usedby facility manager 31 to send commands and data 43 to utilityinformation system 36 and to receive incentives to not opt out or to optin module 42 from utility information system 36. A conveyance medium forthe sending commands and data and receiving messages and data, andincentives to not opt out or to opt in, may be a wireless communicationschannel.

As shown in FIG. 5, a utility 11 may have an information system 36 thatis responsible for interacting with the customer with regards to energyconsumption matters. UIS 36 may be selected from a wide range of systemsand might include a DR management system (DRMS) or some system that isresponsible for sending out dynamic rate information.

When the FM 31 is using MD 33 to interact with utility 11, theinformation that is displayed to FM 31 may be relevant to where FM 31 islocated. Such information may include things such as location specificprices, incentives, requests for bids, DR signals and/or messages.

FM 31 may send commands and data 43 back to utility 11, such as bids orperhaps notifications to opt out or opt in of responses, with or withoutincentives, to DR events. In addition, FM 31 may interact with differentutilities based upon his or her location, especially if FM 31 ismanaging facilities that are in different regions of the country.

In order for the interactions to be location specific, the informationand data from UIS 36 displayed to FM 31 as well as the commands anddata, with incentives to not opt out or to opt in, sent from FM 31should be dependent upon the location of MD 33. This may be accomplishedin the following ways. The location of MD 33 may be determined by UIS36, and UIS 36 may just send information that is relevant to thatlocation. UIS 36 may send out information for virtually all of thepossible locations of MD 33, and MD 33 may just present the informationthat is specific to where it is located at that time.

The approach by which the location of MD 33 is determined mayincorporate all of the well known methodologies in use today for suchpurpose. For example, the approach may incorporate a global positioningsystem (GPS) within MD 33, cellular tower locations, WiFi access pointlocations, WiFi signal strengths, Bluetooth access point locations, andother remote location communication mechanisms.

Furthermore, it may be possible for UIS 36 to determine the location ofMD 33 based upon one of the above methodologies or it may rely on MD 33to determine its own location and transmit the location to UIS 36.

FM 31 may interact with EMS 34 of facility 12, and use wirelesscommunications to do so. The messages and data 45 transmitted from EMS34 to FM 31 may be relevant to the particular loads that FM 31 iscontrolling, and may allow FM 31 to monitor and control EMS 34 in afashion that best optimizes use by EMS 34 the information received fromUIS 36. Examples may incorporate changing thermostat setpoints based onchanging prices from UIS 36.

One may note that FIG. 5 does not necessarily preclude or require ascenario where UIS 36 also communicates with EMS 34 directly as may bethe case with certain automated DR programs. In fact, a role of FM 31 insuch cases may be to make minor adjustments to the EMS 34 automationthat is already programmed into a system.

An approach for influencing demand response event performance through avariable incentive signal may be noted. Automated demand responseprograms may achieve electrical demand reduction by signalingparticipating electricity consumers (human and mechanical) to curtailenergy usage for a certain period of time, commonly referred to as an“event”. Equipment at participating sites may be signaled to changetheir operating state and use less energy than it would under normalcircumstances during the event period. Customers may often be free to“opt-out” and withdraw their participation from DR events, on aper-event basis. When a participant opts out, the total quantity ofenergy savings of the event may be reduced. If too many participants optout, then an ability of the demand response program to produce neededresults may be severely limited.

A core of the approach is that participating customers may be sent amessage offering an incentive to tolerate an ongoing DR event. As anexample, at the beginning of a residential demand response event,communication-enabled room thermostats at participating sites maydisplay a notice that a DR event is in-progress and offer a one dollarreward contingent upon the customer leaving the thermostat undisturbeduntil after a specific time in the future. The customer may be free toopt out anyway, but the customer will not get any reward if the customerdoes so. As the event progresses, the DR operator may monitor itsperformance. If the rate of participant opt-outs is greater thandesired, room thermostats in the still-participating sites may modifytheir display to increase the offer to one dollar and fifty cents, twodollars, or ten dollars provided that the human operator continues tocooperate. Through this mechanism, the DR operator may dynamicallymodulate the rate of opt-outs and therefore the overall productivity ofthe event. In an urgent event, there is not necessarily any limit to thesize of the incentive that can be offered to reduce opt-out performanceleakage.

The productivity of a DR event may be addressed by modifying (i.e.,adding to or removing from) the pool of participating sites in thatevent. If too many participants opt out, additional ones may be broughtinto the event, although they also may very well opt out. The presentapproach may be different in that instead of modulating the number ofparticipants that are included in the event, it may modulate anincentive signal to keep already-included participants from opting out.

A pattern number one may incorporate an opt-out. First, the demandresponse operator may schedule a DR event involving a population ofparticipating sites. Second, an electronic signal may be sent toequipment at each participant site, instructing the equipment to enter astate of reduced energy use (e.g., an air conditioning thermostat set toa higher temperature).

Third, a message may be displayed where each affected customer can seethe message, informing the customer that a load reduction condition isin effect and informs the customer of the incentive offer to leave thecondition undisturbed.

Fourth, some percentage of affected customers may decide that theincentive is not necessarily compelling enough, and choose to opt out ofthe event. Fifth, the demand response program provider may monitor therate of opt-out and decide that the rate is too high. Sixth, a messagemay be displayed where each affected customer can see its changes,informing the customer that the incentive for leaving the equipmentundisturbed is now higher.

Seventh, the percentage of affected customers, who reject the incentiveand opt out, may decline. Eighth, an overall energy reductionperformance of the event may meet the intended goal. Ninth, the end ofthe event period may be reached. An electronic signal may be sent to allparticipating equipment releasing the equipment to return to normaloperation. Tenth, customers who accepted the offer and remained in theevent until its completion should receive their reward.

A pattern number two may incorporate an opt-in. First, the demandresponse operator may schedule a DR event involving a population ofparticipating sites. Second, a message may be displayed where eachaffected customer can see it, informing the customer that a loadreduction condition in effect and informing the customer of theincentive offer if the customer chooses to participate.

Third, some percentage of invited customers may find the incentivecompelling and choose to participate in the event. Fourth, asparticipants accept the incentive, an electronic signal may be sent totheir equipment instructing the equipment to enter a reduced-energystate. Fifth, the demand response program provider may monitor the rateof participation and decide that it is too low.

Sixth, the message may be displayed where each affected customer can seeits changes, informing the customer that the incentive for joining theDR event has been increased. Seventh, the percentage of affectedcustomers who accept the incentive and opt in may increase. Eighth,overall energy reduction performance of the event may meet the intendedgoal.

Ninth, the end of the event period may be reached. An electronic signalmay be sent to all participating equipment releasing the equipment toreturn to normal operation. Tenth, customers who accepted the offer,joined the event, and participated until its completion should receivetheir reward.

It may be noted that participants who choose to opt out forfeit theirincentive. The incentive may only be collected by a participant inchoosing to participate until the end of the event period.

A utility/ISO may enroll customers into demand response (DR) programsand model them as so-called DR resources that the utility can call uponwhen it is necessary for the utility to initiate a DR event. Callingupon a DR resource may typically mean that the utility/ISO sends the DRresource DR signals which affect the DR resource's load consumption insome fashion.

Depending upon the motivating factors for doing DR, a utility/ISO mayattempt to affect a DR resource's load profile in a number of differentways such as: 1) Sending price signals to incentivize the DR resource'sload consumption behavior; 2) Sending specific dispatch instructionsthat dictate the amount of load the DR resource should be consuming; and3) Sending direct load control instructions that put the DR resource'sload control in a specific state, i.e., turn a load on or off.

Specific DR programs may typically have a desired mode of interactionspecified as part of a program design and the mode may be codified intariffs that the owner of the DR resource must conform to if the ownerenrolls in a DR program. Furthermore, the DR signal that is used in aspecific DR program may reflect the desired mode of interaction and thuscontain the appropriate information.

For example, a dynamic pricing program (i.e., mode one above) that isdesigned to cause the customer to shift its load consumption from highpeak times to other times of day may send a price in the DR signal. Inanother example, the DR program may be designed to send dispatchinstructions (i.e., mode two) as part of a so called ancillary serviceto explicitly affect the DR resource's load profile. In this case, theDR signal may contain an explicit load level such as 100 kW.

As noted in the above examples, different DR programs may send DRsignals with fundamentally different types of information in thesignals. An issue is that this approach may put an undue burden on thesystems that must interpret the signals and take the appropriate action,especially if the systems are participating in different DR programsthat may have different signals associated with them. Moving a customerfrom one DR program that uses dynamic pricing signals into a DR programthat uses dispatches may require customers to re-program theirautomation systems to deal with the different DR signals even if theirbasic load control strategies do not change.

The present system and approach may allow a DR resource 12 owner tospecify the DR signals that are sent from the utility/ISO 11 as opposedto the utility/ISO dictating what the signals are. DR resource 12 ownersmay be allowed to create custom signals that are most appropriate fortheir systems and operations. This approach may thus help alleviate aneed for automated load control systems used by a DR resource needing tointerpret different DR signals for different DR programs.

Benefits of the present approach may be the following items: 1) Allowthe DR resource to receive and consume a DR signal that is mostconducive to the way it operates, thus reducing costs to deploy; 2)Reduce the cost of programming the DR resource's load response byallowing the customers to focus their efforts on programming the loadcontrol strategies instead of interpreting and consuming a potentiallywide range of different types of DR signals; 3) Allow the DR resourcesto implement systems with a relatively fixed set of load controlstrategies that can be used without a change in different DR programs,thus reducing complexity and cost; and 4) Allow the utility/ISO to senddifferent types of signals to different DR resources to facilitate theirparticipation in the DR programs.

FIG. 6 is a diagram of a DR scenario in which there is a utility/ISO 11that may utilize a demand response management system (DRMS) 52 formanaging its DR programs to send DR signals 14 to one or more DRresources 12 that are participating in the DR program. DR signal 14 maybe defined by utility/ISO 11 on a per program basis.

DR resource 12 may have some sort of DR interface 55 sub-system thatconsumes DR signals 14 from utility/ISO 11 and in turn forwards messagesor commands to a variety of loads 56 within the facility. Loads 56within the facility may have some sort of controller that can receivemessages and control the load consumption. The controller mayincorporate a processor and/or computer along with a memory and a userinterface. DR interface 55 and loads 56 may be logical entities. DRsignal 14 from utility/ISO 11 may be consumed at the load controlleritself, thus signifying that the DR interface 55 functionality isembedded within the load controller. The number of loads 56 within thefacility can range anywhere from one to many.

The present approach does not depend upon the exact nature of themessages that are sent from the DR interface 55 to loads 56. A point ofrelevancy is that DR signal 14 may be consumed in such a fashion by DRresource 12 that the information in it can be translated into theappropriate load control actions by DR resource 12. Thus, an emphasis ofthe present disclosure may be to support the scenario shown in FIG. 7such that a DR signal 57 that is sent by utility/ISO 11 may have a formand content that is specified by the owner of the DR resource 12 suchthat it can be consumed and translated into the appropriate load controlactions in the most effective fashion as determined by the DR resource12 owners that must deploy and program the systems that are responsiblefor doing the load 56 control.

FIG. 8 is a diagram showing a DRMS 52 with subsystems that allowcustomers to specify their own DR signals 57. DRMS 52 may performvirtually all its normal operations and generate a utility defined DRsignal 14 as shown by a “normal signal generator” sub-system 58. Signal14 may be passed through a sub-system referred to as the “customerdefined signal translation” sub-system 59. Within sub-system 59 may be aset of user defined rules that are specific to a DR program that willtake a DR signal 19 that is specific to that program and translate itinto some form of a DR signal 57 as specified by the customer.

As indicated in FIG. 8, there may be DR resource operator 61 that mayprovides information via, for instance, a user interface 63 and aconnection 62, relative a DR signal configuration, that supports thefollowing functions. First, there may be an ability to specify the formand possible values for a customer or user defined signal 57. A signalthat is defined by the customer may be designed to make it as easy toconsume by DR resource 12 and may be based upon the capabilities of theload 56 control systems within the DR resource 12 facility. These customDR signals 57 may or may not be dependent upon specific DR programs.Second, there may be a set of DR program specific rules that translatethe possible values of the utility specified DR signals 14 into thecustomer defined set of DR signals 57.

As way of example, one may assume that there is a facility that containsa range of loads such as HVAC, lighting, freezer units, electricvehicles, and so on, and the entire facility may be offered to theutility/ISO 11 as a single DR resource 12. In order to simplify thecreation of DR load control strategies, the facility manager may createa set of five different load consumption levels for the entire facilityand program the control of the individual loads as they relate to eachof the five different levels. For example, perhaps at level one, halfthe thermostats may be set back one degree and certain lights may beturned off. DR resource operator 61 may then interface to DRMS 52 tocreate a customer specific DR signal that may contain five levels, onefor each of the levels that have been programmed into the controlsystem. Thus, when DR resource 12 receives a DR signal 57 with one ofthe levels, the proper DR control strategies are already programmed intothe system and easy to perform. Operator 61 may need only to specifywithin DRMS 52 a set of rules. The amount of load consumption levels maybe set at virtually any number.

To recap, a system, for predicting a DR load response for a resource toa DR signal, may incorporate a utility/ISO and a demand resource. Theutility may send a DR signal to a demand resource. The DR signal may beconveyed at a predefined finite value. The DR resource may report back adescription of a load response that is predictable according to the DRsignal at the predefined finite value.

The DR resource may continuously report back to the utility/ISO as towhat a load response is to be according to a DR signal having apredefined finite value. The resource continuously reporting back to theutility/ISO may provide predictability of a load response relative to apredefined finite value of the DR signal.

The system may further incorporate a user interface of the utility/ISOthat provides DR signals to and receives feedback from the DR resource.A selection of a predefined finite level of DR signal may be dispatchedto the DR resource. The DR resource may respond with a load responserelative to the predefined finite level of the DR signal. The predefinedfinite level of the DR signal may incorporate two or more levels ofdispatch.

The DR resource may be in constant communication with a DR managementsystem. The DR response may continuously report what a load response inunits of power will be if the DR response receives a DR signal having apredefined finite value.

A display may show an actual load response versus time for the DRresource receiving a DR signal in the past. The display may show aprojection for a future.

For the future, the projection by the utility/ISO may incorporatevarious load responses based on feedback received from the DR resource.Additional DR resources may be aggregated for showing actual loadresponse versus time for the DR resources in the past and with aprojection of load responses for the future.

Values of the responses of the DR resources for each signal type may beadded together resulting in N levels of dispatches. There may be Xnumber of resources. Each resource may operate at N levels of dispatchesresulting in a number of settings on an order of X to a power of N.

A system, for predicting load responses from resources relative todemand response signals, may incorporate a utility, and a demandresponse (DR) resource having a communication connection with theutility. A DR signal may be sent via the communication connection fromthe utility to the DR resource. A current state of loads of the DRresource may be determined by the DR signal.

Predictability of a load response of a DR resource to a DR signal may bedependent upon when the DR signal is restricted to one of a set ofpredefined finite values and for each of the predefined finite valuessent as a DR signal, the DR resource may continuously report back whatits load response will be.

A demand response and comfort system may incorporate a utility/ISO and ademand response (DR) resource. The utility/ISO may send DR signals tothe DR resource having a first degree of comfort. The DR signals maycause a reduction of the first degree of comfort to a second degree ofcomfort, or vice versa, during a DR event initiated by the utility/ISO.

The DR resource may have a recovery rate to a former degree of comfort.The recovery rate may incorporate the first degree of comfort minus thesecond degree of comfort divided by an amount to time to reduce adifference of the first degree of comfort and the second degree ofcomfort to zero.

The first degree of comfort may be a temperature as indicated by athermostat setting at the DR resource. The second degree of comfort maybe a temperature at the DR resource.

The recovery rate of a resource may be used by the utility/ISO inshedding a certain amount of energy.

The utility may select the second degree of comfort and the amount oftime to reduce the difference of the first degree of comfort and thesecond degree of comfort to zero after termination of the DR event.

In the present specification, some of the matter may be of ahypothetical or prophetic nature although stated in another manner ortense.

Although the present system and/or approach has been described withrespect to at least one illustrative example, many variations andmodifications will become apparent to those skilled in the art uponreading the specification. It is therefore the intention that theappended claims be interpreted as broadly as possible in view of therelated art to include all such variations and modifications.

What is claimed is:
 1. A system, for predicting a demand response (DR)load response for a resource to a DR signal, comprising: autility/independent system operator (ISO); and a demand resource; andwherein: the utility sends a DR signal to a demand resource; the DRsignal is conveyed at a predefined finite value; and the DR resourcereports back a description of a load response that is predictableaccording to the DR signal at the predefined finite value.
 2. The systemof claim 1, wherein: the DR resource continuously reports back to theutility/ISO as to what a load response is to be according to a DR signalhaving a predefined finite value; and the resource continuouslyreporting back to the utility/ISO provides predictability of a loadresponse relative to a predefined finite value of the DR signal.
 3. Thesystem of claim 1, further comprising: a user interface of theutility/ISO that provides DR signals to and receives feedback from theDR resource; and wherein a selection of a predefined finite level of aDR signal is dispatched to the DR resource.
 4. The system of claim 3,wherein the DR resource responds with a load response relative to thepredefined finite level of the DR signal.
 5. The system of claim 2,wherein the predefined finite level of the DR signal comprises two ormore levels of dispatch.
 6. The system of claim 1, wherein: the DRresource is in constant communication with a DR management system; andthe DR response continuously reports what a load response in units ofpower will be if the DR response receives a DR signal having apredefined finite value.
 7. The system of claim 1, wherein: a displayshows an actual load response versus time for the DR resource receivinga DR signal in the past; and the display shows a projection for afuture.
 8. The system of claim 7, wherein for the future, the projectionby the utility/ISO comprises various load responses based on feedbackreceived from the DR resource.
 9. The system of claim 8, whereinadditional DR resources are aggregated for showing actual load responseversus time for the DR resources in the past and with a projection ofload responses for the future.
 10. The system of claim 9, wherein:values of the responses of the DR resources for each signal type areadded together resulting in N levels of dispatches.
 11. The system ofclaim 10, wherein: there are X number of resources; and each resourcecan operate at N levels of dispatches resulting in a number of settingson an order of X to a power of N.
 12. A system for predicting loadresponses from resources relative to demand response signals,comprising: a utility; and a demand response (DR) resource having acommunication connection with the utility; and wherein a DR signal issent via the communication connection from the utility to the DRresource.
 13. The system of claim 12, wherein a current state of loadsof the DR resource is determined by the DR signal.
 14. The system ofclaim 12, wherein predictability of a load response of a DR resource toa DR signal is dependent upon when the DR signal is restricted to one ofa set of predefined finite values and for each of the predefined finitevalues sent as a DR signal, the DR resource continuously reports backwhat its load response will be.
 15. A demand response and comfort systemcomprising: a utility/ISO; and a demand response (DR) resource; andwherein: the utility/ISO sends DR signals to the DR resource having afirst degree of comfort; and the DR signals cause a reduction of thefirst degree of comfort to a second degree of comfort, or vice versa,during a DR event initiated by the utility/ISO.
 16. The system of claim15, wherein the DR resource has a recovery rate to a former degree ofcomfort.
 17. The system of claim 16, wherein the recovery rate comprisesthe first degree of comfort minus the second degree of comfort dividedby an amount to time to reduce a difference of the first degree ofcomfort and the second degree of comfort to zero.
 18. The system ofclaim 17, wherein: the first degree of comfort is a temperature asindicated by a thermostat setting at the DR resource; and the seconddegree of comfort is a temperature at the DR resource.
 19. The system ofclaim 17, wherein the recovery rate of a resource is used by theutility/ISO in shedding a certain amount of energy.
 20. The system ofclaim 17, the utility selects the second degree of comfort and theamount of time to reduce the difference of the first degree of comfortand the second degree of comfort to zero after termination of the DRevent.